Applied Scientist (AI)

TL;DR

Applied Scientist (Embodied AI): Developing next-generation AI systems for autonomous driving with an accent on world modeling, representation learning, and scalable decision-making. Focus on building realistic simulators, advancing spatial intelligence, and optimizing sim-to-real transfer.

Location: Hybrid in Vancouver, Canada. Relocation support with visa sponsorship is available.

Company

hirify.global is a leading developer of Embodied AI technology creating mapless and hardware-agnostic AI products for automakers to accelerate the transition to automated driving.

What you will do

• Develop world models and planners using diffusion-based, autoregressive, or hybrid approaches for realistic simulation.
• Advance reinforcement learning and reward modeling, building scalable learning frameworks across real and synthetic data.
• Create geometric foundation models for 3D spatial understanding in dynamic, real-world environments.
• Enable cross-embodiment robotics by leveraging multimodal foundation models to accelerate learning on diverse platforms.
• Conduct empirical research on scaling laws, generalization, and sim-to-real transfer.
• Define and evolve evaluation frameworks and benchmarks for long-horizon prediction and driving performance.

Requirements

• 3+ years of experience developing and deploying ML systems in real-world or production settings.
• PhD, Master’s degree, or equivalent experience in Machine Learning, Computer Vision, Robotics, or a related field.
• Deep expertise in foundation models, generative world modeling, RL, or Spatial AI.
• Track record of publications at top-tier conferences such as NeurIPS, ICML, ICLR, CVPR, ICCV, or CoRL.
• Strong programming skills in Python and experience with PyTorch.
• Must be based in or be able to relocate to Vancouver, Canada.

Nice to have

• Experience in autonomous driving, robotics, or simulation systems.
• Familiarity with large-scale training tools like FSDP, DeepSpeed, or JAX.
• Experience with sim-to-real transfer or data-efficient learning.
• Contributions to open-source ML tools or research infrastructure.

Culture & Benefits

• Attractive compensation including salary and equity.
• Relocation support with visa sponsorship.
• Hybrid working policy with flexible hours.
• Comprehensive onsite perks: chef, workplace nursery scheme, private health insurance, therapy, and daily yoga.
• Immersion in a world-class team of researchers, engineers, and entrepreneurs.
• Unlimited L&D requests and bespoke learning opportunities.